Bio-Inspired AI
Building intelligence inspired by biology
Developing AI systems that learn and adapt like biological neural networks.
Overview
We draw from neuroscience and biological systems to create more robust, efficient, and interpretable AI architectures. Our research explores how principles from neural computation — including attention mechanisms, hierarchical processing, and continual learning — can advance machine intelligence for healthcare applications.
Active Projects
Neural Architecture Search for Medical AI
Designing brain-inspired architectures that improve diagnostic accuracy while maintaining clinical interpretability.
Biological Attention Mechanisms
Implementing attention systems inspired by visual cortex processing for medical image analysis and pattern recognition.
Continual Learning for Clinical Systems
Developing AI that adapts to new medical knowledge without catastrophic forgetting, inspired by hippocampal memory consolidation.